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SEA Multilingual Document Summarizer

对英语、中文、马来语和印尼语文档生成简要、详细或行动项式摘要,支持跨语言翻译摘要,并抽取人名、机构、金额、日期和地点等实体,以 JSON 返回;使用前需先调用外部计费端点完成付费授权,摘要本身由宿主模型能力完成。

wms2537
wms2537
热度 65.12
最近更新 2026-05-11 17:29:14
分类:效率依赖:第三方 API / 内部调用大模型应用场景:摘要总结 / 翻译

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add sea-doc-summarizer
Metadata
name
sea-doc-summarizer
description
Summarize documents in EN/CN/BM/ID with cross-language support. Optimized for Southeast Asian languages.
version
2.0.0
metadata
{"openclaw":{"requires":{"env":["SKILLPAY_API_KEY"]},"emoji":"📝"}}

SEA Multilingual Document Summarizer

Summarize documents across English, Chinese, Bahasa Malaysia, and Bahasa Indonesia with cross-language support.

How to Use This Skill

Step 1: Charge billing

POST to the skill endpoint to authorize payment:

POST https://sea-doc-summarizer.swmengappdev.workers.dev/charge
Content-Type: application/json

{"user_id": "<user_id>"}

If successful, you'll receive {"success": true}. If payment fails, you'll receive a payment_url to share with the user.

Step 2: Detect source language

Use these heuristics to detect the document language:

  • Chinese (zh): More than 30% of characters are CJK (Unicode range \u4e00-\u9fff)
  • Bahasa Malaysia (ms): High frequency of words: dan, yang, untuk, dalam, dengan, ini, itu, adalah, telah, akan
  • Bahasa Indonesia (id): Similar to MS but with specific markers: dari, pada, sudah, belum, bisa, harus
  • English (en): Default if none of the above match

Step 3: Summarize the document

Using your own capabilities, summarize the document according to the requested style:

Style: brief Provide 3-5 bullet points summarizing the key information.

Style: detailed Provide a comprehensive paragraph summary covering all important details.

Style: action_items Extract action items, deadlines, and next steps as a bullet list.

Cross-language summarization: If the target language differs from the source, translate the summary. For example, a Chinese document can be summarized in English.

Language-specific tips:

  • For BM/ID documents: Pay attention to formal vs informal register
  • For CN documents: Handle both Simplified and Traditional Chinese
  • For mixed-language documents (common in MY/SG): Identify the primary language

Step 4: Extract entities

Also extract named entities from the document:

  • People names
  • Company/organization names
  • Monetary amounts (with currency)
  • Dates and deadlines
  • Locations

Output Format

Return the summary as JSON:

{
  "summary": "The summarized text here",
  "key_points": ["Point 1", "Point 2", "Point 3"],
  "entities": [
    {"name": "Petronas", "type": "company"},
    {"name": "RM 1.5 million", "type": "amount"}
  ],
  "source_lang": "ms",
  "word_count": {
    "original": 500,
    "summary": 80
  }
}

Pricing

$0.005 USDT per call via SkillPay.me